International Business Machines Corporation

Ratul Sarkar

Srinivasan S Muthuswamy

Ankit Kumar Singh

Subhendu Das

Mandar Mutalikdesai

Yashodhara M Patnaik

Sheetal Srivastava

Simardeep Singh Arneja

Pranjal Srivastava

Noor Mohammed Ashrafi

A system, computer program product, and method are presented for leveraging structured data and unstructured data, and, more specifically, to ranking documentation from unstructured data sources through leveraging insights provided by the structured data to facilitate associated business risk inquiries. The method includes identifying, by researching subject business entities, one or more structured data sources that include relevant structured data directed to the subject business entities. The method also include extracting the relevant structured data directed toward the subject business entities and leveraging the relevant structured data to identify unstructured data sources. The method further includes identifying documents from the unstructured data sources that have relevant information, thereby identifying relevant unstructured data, and leveraging the relevant structured data to determine relationships with the relevant unstructured data. The method also includes scoring each relationship and ranking each document from the unstructured data sources as a function of the scoring.

Leveraging structured data to rank unstructured data

A computer-implemented system, method and/or computer program product to monitor changes in business risk of a targeted entity includes retrieving one or more industry classifications for one or more core businesses of the targeted entity; receiving news feeds related to the one or more industry classifications; detecting and extracting negative news related to the core businesses of the targeted entity from the news feeds; calculating an industry confidence score based upon the negative news; determining if the industry confidence score is greater than an industry confidence threshold; calculating, in response to the industry confidence score being larger than the industry confidence threshold, an entity confidence score for the targeted entity based upon negative news; and generating, in response to the entity confidence score being larger than an entity confidence threshold, an alert report for the targeted entity.

System and method to monitor relevance of customer's business risk due to market changes

A system and associated method provides a visualization of a life cycle of a trade order. The visualization may be in the form of a tree structure with a plurality of linked nodes. Each node may be associated with an event that occurs during the life cycle of the trade. A monitoring system receives information associated with a plurality of events associated with the trade order, generates a plurality of nodes based on the received information, stores identifiers associated with each of the plurality of nodes, and links the plurality of nodes based on the identifiers to create the tree structure. The monitoring system also performs a verification process to determine whether the visualization is missing information or includes incorrect information and alerts to a discrepancy identified during the verification process.

Systems and methods for visualizing a trade life cycle and detecting discrepancies

A computer categorizes a news article by an activity and an associated activity phase, includes receiving, by a computer, at least one news article from an article source. The computer assigns for each news article, an activity of focus selected from a list of target activities, using a first machine learning model. The computer identifies, for each news article, at least one activity phase candidate selected from a list of activity phases associated with the activity of focus, using a second machine learning model. The computer determines, for each of new article, an activity phase of focus from among the activity phase candidates. The determination is based, at least in part on a confirmation attribute associated with the article. The computer categorizes each of the articles by said activity of focus and said activity phase of focus.

Computerized grouping of news articles by activity and associated phase of focus

A mixing pattern system for networks is provided. One or more nodes in a network are analyzed. Grouping the one or more nodes into one or more classes within the network. A computer device analyzes one or more transactions between the one or more nodes in the network that include nodes within similar or distinct classes of the one or more nodes. A computer device identifies one or more mixing patterns associated with one or more transactions between the one or more nodes.

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Bengaluru, India

Ratul Sarkar